The effects of immune-age on immune-response and the molecular mechanisms which drive it

项目摘要 免疫系统是一个复杂的系统，它不断变化，因为它响应于内部和外部 环境，使得很难理解个体之间的差异及其功能 影响我们的SELA衍生轨迹捕获了个体之间免疫细胞组成的变化， 从而描述了在健康衰老过程中发生的细胞组成变化的保守级联。一个 个体的高维免疫细胞组成可以被转化为定量测量， 它的位置沿着这个反映免疫年龄的免疫老化级联。个体的免疫年龄随着他们 以不同的速率沿着这种模式化的轨迹前进，导致基线处的个体间差异很大。 我们假设，由于表观遗传细胞特异性，免疫老化轨迹在个体之间是保守的。 通过与常见的生理和环境变化相互作用而引起的变化， 随着年龄的增长而发生。此外，我们假设这是个体之间免疫年龄的基线变化， 在免疫应答过程中具有功能性影响，最终可能导致临床结果的变异性， 这在大多数损伤和治疗中观察到。项目1旨在丰富和完善我们的免疫 通过扩大我们的队列（增加40-60岁的双胞胎）和测量额外的免疫细胞来衡量年龄指标 发现与免疫相关的类型、因素（细胞因子、表观遗传修饰和代谢组学） 衰老此外，我们将确定驱动免疫年龄轨迹沿着进展的因素。此外，本发明还提供了一种方法， 我们将全面了解年龄和免疫史影响适应性（B和T）反应的方式 老年人每年接种流感疫苗。最后，利用12年以上的生物库SELA样本， 在季节性流感疫苗接种前后，我们将检验分子免疫应答不同的假设， 作为由不同疫苗引起的基线免疫年龄和解耦免疫动力学的函数 由免疫老化引起的组合物。我们将联合收割机结合后者的分子特征 将免疫年龄与流感特异性适应性反应的数据相关联， 全面了解老年人的疫苗反应，这是一个感染的风险群体。我们希望 将免疫年龄与B和T流感病史相结合，将允许从基线预测流感疫苗应答， 这是一个尚未解决的世界卫生问题。

PROJECT SUMMARY The immune system is a complex system which continuously changes as it responds to the internal and external environments, making it very difficult to understand the variation between individuals and its functional implications. Our SELA derived trajectory captures the variation in immune-cell composition between individuals, thus describes the conserved cascade of cell compositional changes occurring during healthy aging. An individual’s high-dimensional immune cell composition can be translated into a quantitative measure describing its position along this immune-aging cascade reflecting the immune-age. Individuals’ immune-age alters as they advance at different rates along this patterned trajectory, resulting in high inter-individual variation at baseline. We hypothesize that the immune-aging trajectory is conserved between individuals due to epigenetic cell-specific alterations that are induced through an interaction with common physiological and environmental changes that occur with age. Furthermore, we hypothesize that this the baseline variation in immune-age between individuals has functional implications during immune response, which ultimately may lead to variability in clinical outcome, which is observed for the majority of insults and therapies. Project 1 is designed to enrich and refine our immune age metric by expanding our cohort (adding 40-60 years-old twins) and by measuring in addition immune cell types, factors (cytokines, epigenetic modifications, and metabolomics) found to be in correlation with immune aging. Furthermore, we will identify factors that drive progression along the immune age trajectory. In addition, we will gain comprehensive insight into the way age and immune history affect adaptive (B and T) responses elicited by annual influenza vaccination in the old. Lastly, leveraging the 12+ years of bio-banked SELA samples pre and post seasonal influenza vaccination we will test the hypothesis that molecular immune responses differ as a function of baseline immune-age and decouple immune dynamics that are caused by different vaccine compositions from those that are caused by immune-age. We will combine the latter molecular features correlated with immune age with data on flu specific adaptive responses to obtain, for the first-time comprehensive understanding of vaccine responses in older adults, a risk group for infection. We hope that combining immune-age with B and T flu history, will allow to predict influenza vaccine response from baseline, an unsolved problem of high concern for world health.